A Reliable and Rapid Language Tool for the Diagnosis, Classification, and Follow-Up of Primary Progressive Aphasia Variants

Advancing Neuropsychological Rehabilitation in Primary Progressive Aphasia Based on Principles of Cognitive Neuroscience: A Scoping Review and Systematic Analysis of the Data

Background/Objectives: This systematic review of neuropsychological rehabilitation strategies for primary progressive aphasia will consider recent developments in cognitive neuroscience, especially neuroimaging techniques such as EEG and fMRI, to outline how these tools might be integrated into clinical practice to maximize treatment outcomes. Methods: A systematic search of peer-reviewed literature from the last decade was performed following the PRISMA guidelines across multiple databases. A total of 63 studies were included, guided by predefined inclusion and exclusion criteria, with a focus on cognitive and language rehabilitation in PPA, interventions guided by neuroimaging, and mechanisms of neuroplasticity. Results: Integration of neuroimaging techniques contributes to the increase in the efficacy of interventions with critical information about the neural mechanisms underlying language deficits in the aphasias. Traditional rehabilitation strategies, technology-assisted interventions, and non-invasive brain stimulation techniques hold considerable promise for language improvement. Neuroimaging was also found to be necessary in subtype-specific differentiation toward tailoring therapeutic intervention. Evidence also shows that directed and sustained interventions using neuroplasticity can have long-term effects in managing the symptoms of PPA. Conclusions: The present review underlines the necessity of including cognitive neuroscience techniques within neuropsychological rehabilitation to enhance therapeutic outcomes in PPA. In addition, neuroimaging modalities such as EEG and fMRI are also of great importance in understanding the underlying neurobiology of language disturbances and guiding tailored interventions. Long-term benefits of these approaches should be evaluated, including their applicability in routine clinical practice.

Applications of the R.A.I.S.E. Assessment Framework to Support the Process of Assessment in Primary Progressive Aphasia

PURPOSE

To establish the extent to which person-centered processes are integrated in assessment procedures, the Relationship, Assessment, Inclusion, Support, Evolve (R.A.I.S.E.) Assessment framework was used to evaluate measures that are typically used when assessing people living with primary progressive aphasia (PPA).

METHOD

Forty-five assessment tools were evaluated through the lens of the five R.A.I.S.E. principles: building the client-clinician Relationship, Assessment choices, Including the client and care partners, providing Support, and Evolving procedures to match client capability and progression. The principles were operationalized as questions for raters to evaluate whether a measure met this aspect of the R.A.I.S.E. Assessment framework.

RESULTS

Ten measures commonly used in the assessment of people living with PPA met all R.A.I.S.E. principles. These measures centered upon the elicitation of naturalistic discourse, conversation, client self-report, and clinician ratings. Thirteen measures did not meet any of the criteria, and represented standardized evaluation procedures do not provide the opportunity to connect to the client, elicit or provide feedback or support, nor to adapt in response to need or performance.

CONCLUSIONS

Whether using standardized or informal assessment tools, a relational and qualitative approach to providing assessment is paramount to promote client success and therapeutic engagement. We provide guidance through the R.A.I.S.E. framework on practices to cultivate person-centered processes of assessment in the care of people living with PPA.

Patterns of performance on the animal fluency task in logopenic variant of primary progressive aphasia: A reflection of phonological and semantic skills

PURPOSE

This study aimed to characterize the quantitative (total number of correct words generated) and qualitative (psycholinguistic properties of correct words generated) performance patterns on the animal fluency task in individuals with the logopenic variant of primary progressive aphasia and to investigate the influence of phonological and semantic abilities to these patterns.

METHODS

Fifteen participants with lvPPA and twenty neurotypical adults completed the animal fluency task and an assessment battery to characterize their phonological and semantic abilities. We recorded the total number of correct words produced and their psycholinguistic properties. Group differences were analyzed using independent samples t-tests and analysis of covariance. Stepwise and multiple linear regression analyses were implemented to investigate the contribution of psycholinguistic properties on word generation as well as the role of phonological and semantic abilities on performance. We also investigated the mediating role of phonological and semantic abilities on the relationship between relevant psycholinguistic properties and word generation output.

RESULTS

Compared to neurotypical controls, participants with lvPPA produced fewer correct responses and more words with lower age of acquisition. The total number of correct words generated was predicted by the age of word acquisition, such that individuals who generated more responses, produced words acquired later in life. Phonology and semantics influenced the number of correct words generated and their frequency, age of acquisition, and semantic neighborhood density. Familiarity and arousal were driven by semantic abilities. Phonological abilities partially mediated the relationship between age of acquisition and word generation output.

CONCLUSIONS

This study provides valuable insights into the performance patterns of the animal fluency task in lvPPA. Individuals with lvPPA with more intact phonological and semantic abilities generated greater number of words with more complex psycholinguistic properties. Our findings contribute to the understanding of language processes underlying word retrieval in lvPPA.

Characterization of the logopenic variant of Primary Progressive Aphasia: A systematic review and meta-analysis

The linguistic and anatomical variability of the logopenic variant of Primary Progressive Aphasia (lv-PPA) as defined by current diagnostic criteria has been the topic of an intense debate. The present review and meta-analysis aims at characterizing the profile of lv-PPA, by a comprehensive analysis of the available literature on the neuropsychological, neuroimaging, electrophysiological, pathological, and genetic features of lv-PPA. We conducted a systematic bibliographic search, leading to the inclusion of 207 papers. Of them, 12 were used for the Anatomical Likelihood Estimation meta-analysis on grey matter revealed by magnetic resonance imaging data. The results suggest that the current guidelines outline a relatively consistent syndrome, characterized by a core set of linguistic and, to a lesser extent, non-linguistic deficits, mirroring the involvement of left temporal and parietal regions typically affected by Alzheimer Disease pathology. Variations of the lv-PPA profile are discussed in terms of heterogeneity of the neuropsychological instruments and the diagnostic criteria adopted.

A Telemedicine Platform for Aphasia: Protocol for a Development and Usability Study

BACKGROUND

Aphasia is a central disorder of comprehension and expression of language that cannot be attributed to a peripheral sensory deficit or a peripheral motor disorder. The diagnosis and treatment of aphasia are complex. Interventions that facilitate this process can lead to an increase in the number of assisted patients and greater precision in the therapeutic choice by the health professional.

OBJECTIVE

This paper describes a protocol for a study that aims to implement a computer-based solution (ie, a telemedicine platform) that uses deep learning to classify vocal data from participants with aphasia and to develop serious games to treat aphasia. Additionally, this study aims to evaluate the usability and user experience of the proposed solution.

METHODS

Our interactive and smart platform will be developed to provide an alternative option for professionals and their patients with aphasia. We will design 2 serious games for aphasia rehabilitation and a deep learning-driven computational solution to aid diagnosis. A pilot evaluation of usability and user experience will reveal user satisfaction with platform features.

RESULTS

Data collection began in June 2022 and is currently ongoing. Results of system development as well as usability should be published by mid-2023.

CONCLUSIONS

This research will contribute to the treatment and diagnosis of aphasia by developing a telemedicine platform based on a co-design process. Therefore, this research will provide an alternative method for health care to patients with aphasia. Additionally, it will guide further studies with the same purpose.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/40603.

Neuroanatomical correlates of screening for aphasia in NeuroDegeneration (SAND) battery in non-fluent/agrammatic variant of primary progressive aphasia

Background

Non-fluent/agrammatic variant of Primary Progressive Aphasia (avPPA) is primarily characterized by language impairment due to atrophy of the inferior frontal gyrus and the insula cortex in the dominant hemisphere. The Screening for Aphasia in NeuroDegeneration (SAND) battery has been recently proposed as a screening tool for PPA, with several tasks designed to be specific for different language features. Applying multivariate approaches to neuroimaging data and verbal fluency tasks, Aachener Aphasie Test (AAT) naming subtest and SAND data may help in elucidating the neuroanatomical correlates of language deficits in avPPA.

Objective

To investigate the neuroanatomical correlates of language deficits in avPPA using verbal fluency tasks, AAT naming subtest and SAND scores as proxies of brain structural imaging abnormalities.

Methods

Thirty-one avPPA patients were consecutively enrolled and underwent extensive neuropsychological assessment and MRI scan. Raw scores of verbal fluency tasks, AAT naming subtest, and SAND subtests, namely living and non-living picture naming, auditory sentence comprehension, single-word comprehension, words and non-words repetition and sentence repetition, were used as proxies to explore structural (gray matter volume) neuroanatomical correlates. We assessed univariate (voxel-based morphometry, VBM) as well as multivariate (source-based morphometry, SBM) approaches. Age, gender, educational level, and disease severity were considered nuisance variables.

Results

SAND picture naming (total, living and non-living scores) and AAT naming scores showed a direct correlation with the left temporal network derived from SBM. At univariate analysis, the left middle temporal gyrus was directly correlated with SAND picture naming (total and non-living scores) and AAT naming score. When words and non-words repetition (total score) was considered, a direct correlation with the left temporal network (SBM) and with the left fusiform gyrus (VBM) was also evident.

Conclusion

Naming impairments that characterize avPPA are related to specific network-based involvement of the left temporal network, potentially expanding our knowledge on the neuroanatomical basis of this neurodegenerative condition.

Italian translation and cross-cultural adaptation of the Progressive Aphasia Severity Scale

Primary progressive aphasia (PPA) is a neurodegenerative disease characterised by a progressive decline in language and speech as the first clinical manifestation, which mostly spares other cognitive functions. However, the linguistic impairment of PPA shows different features than that resulting from cerebrovascular diseases. The major difference between the linguistic manifestations of PPA and the traditional classification of aphasias has led to the development of new, more specific methods of language assessment. Among the currently available tools, there has been great interest in the Progressive Aphasia Severity Scale (PASS). This quick and easy-to-use clinical tool allows to collect significant information from caregivers about the communicative, linguistic, and functional difficulties of patients affected by PPA. In addition to monitoring the severity and progression of deficits in 13 different language domains, this scale integrates the classic "clinically reported" assessment with a "caregiver-reported" analysis of the daily experience of the patient, which provides a better understanding of how the disease affects the quality of life of both the patient and the caregiver. In the present contribution, the PASS was translated and adapted into Italian according to the international guidelines for the cross-cultural adaptation of self-report measures. This version of the PASS can help clinicians and researchers in the diagnosis of PPA in Italian clinical populations. Furthermore, it could be particularly useful for the long-term evaluation of the disease, in order to monitor its evolution, and might represent an optimal means to verify the efficacy of speech/language therapy in delaying the progression of the disease.

Application of Machine Learning to Electroencephalography for the Diagnosis of Primary Progressive Aphasia: A Pilot Study

Background. Primary progressive aphasia (PPA) is a neurodegenerative syndrome in which diagnosis is usually challenging. Biomarkers are needed for diagnosis and monitoring. In this study, we aimed to evaluate Electroencephalography (EEG) as a biomarker for the diagnosis of PPA. Methods. We conducted a cross-sectional study with 40 PPA patients categorized as non-fluent, semantic, and logopenic variants, and 20 controls. Resting-state EEG with 32 channels was acquired and preprocessed using several procedures (quantitative EEG, wavelet transformation, autoencoders, and graph theory analysis). Seven machine learning algorithms were evaluated (Decision Tree, Elastic Net, Support Vector Machines, Random Forest, K-Nearest Neighbors, Gaussian Naive Bayes, and Multinomial Naive Bayes). Results. Diagnostic capacity to distinguish between PPA and controls was high (accuracy 75%, F1-score 83% for kNN algorithm). The most important features in the classification were derived from network analysis based on graph theory. Conversely, discrimination between PPA variants was lower (Accuracy 58% and F1-score 60% for kNN). Conclusions. The application of ML to resting-state EEG may have a role in the diagnosis of PPA, especially in the differentiation from controls. Future studies with high-density EEG should explore the capacity to distinguish between PPA variants.